original_glue_boolq / README.md
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metadata
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
  - trl
  - sft
  - generated_from_trainer
datasets:
  - super_glue
metrics:
  - accuracy
model-index:
  - name: original_glue_boolq
    results: []

original_glue_boolq

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.1 on the super_glue dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3297
  • Accuracy: 0.8700

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 2
  • eval_batch_size: 4
  • seed: 2
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • total_eval_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4632 0.05 50 0.4840 0.7958
0.3453 0.1 100 0.3888 0.8226
0.2722 0.15 150 0.3590 0.8396
0.3266 0.2 200 0.3811 0.8459
0.3699 0.25 250 0.3534 0.8438
0.3554 0.3 300 0.3378 0.8565
0.1229 0.35 350 0.3368 0.8643
0.3522 0.4 400 0.3424 0.8643
0.2548 0.45 450 0.3467 0.8664
0.2119 0.5 500 0.3439 0.8714
0.2113 0.55 550 0.3518 0.8657
0.2122 0.6 600 0.3110 0.8770
0.3251 0.65 650 0.3323 0.8728
0.2904 0.7 700 0.3152 0.8792
0.6366 0.75 750 0.3502 0.8763
0.4161 0.8 800 0.3250 0.8806
0.1605 0.85 850 0.3258 0.8834
0.271 0.9 900 0.3330 0.8848

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0